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linode/linode_api4-python | linode_api4/linode_client.py | ProfileGroup.ssh_key_upload | def ssh_key_upload(self, key, label):
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:param key: The ssh key, or a path to the ssh key. If a path is provided,
the file at the path must exist and be readable or an ... | python | def ssh_key_upload(self, key, label):
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linode/linode_api4-python | linode_api4/linode_client.py | LongviewGroup.client_create | def client_create(self, label=None):
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linode/linode_api4-python | linode_api4/linode_client.py | AccountGroup.events_mark_seen | def events_mark_seen(self, event):
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linode/linode_api4-python | linode_api4/linode_client.py | AccountGroup.settings | def settings(self):
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linode/linode_api4-python | linode_api4/linode_client.py | AccountGroup.oauth_client_create | def oauth_client_create(self, name, redirect_uri, **kwargs):
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linode/linode_api4-python | linode_api4/linode_client.py | AccountGroup.transfer | def transfer(self):
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linode/linode_api4-python | linode_api4/linode_client.py | AccountGroup.user_create | def user_create(self, email, username, restricted=True):
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linode/linode_api4-python | linode_api4/linode_client.py | NetworkingGroup.ips_assign | def ips_assign(self, region, *assignments):
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linode/linode_api4-python | linode_api4/linode_client.py | NetworkingGroup.ip_allocate | def ip_allocate(self, linode, public=True):
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:type linode: Instance or int
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linode/linode_api4-python | linode_api4/linode_client.py | NetworkingGroup.shared_ips | def shared_ips(self, linode, *ips):
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient.load | def load(self, target_type, target_id, target_parent_id=None):
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient._api_call | def _api_call(self, endpoint, model=None, method=None, data=None, filters=None):
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient.image_create | def image_create(self, disk, label=None, description=None):
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient.nodebalancer_create | def nodebalancer_create(self, region, **kwargs):
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient.domain_create | def domain_create(self, domain, master=True, **kwargs):
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Registers a new Domain on the acting user's account. Make sure to point
your registrar to Linode's nameservers so that Linode's DNS manager will
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:param domain: The domain to register to Lin... | python | def domain_create(self, domain, master=True, **kwargs):
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient.tag_create | def tag_create(self, label, instances=None, domains=None, nodebalancers=None,
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Creates a new Tag and optionally applies it to the given entities.
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linode/linode_api4-python | linode_api4/linode_client.py | LinodeClient.volume_create | def volume_create(self, label, region=None, linode=None, size=20, **kwargs):
"""
Creates a new Block Storage Volume, either in the given Region or
attached to the given Instance.
:param label: The label for the new Volume.
:type label: str
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linode/linode_api4-python | linode_api4/login_client.py | LinodeLoginClient.generate_login_url | def generate_login_url(self, scopes=None, redirect_uri=None):
"""
Generates a url to send users so that they may authenticate to this
application. This url is suitable for redirecting a user to. For
example, in `Flask`_, a login route might be implemented like this::
@app.r... | python | def generate_login_url(self, scopes=None, redirect_uri=None):
"""
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linode/linode_api4-python | linode_api4/login_client.py | LinodeLoginClient.finish_oauth | def finish_oauth(self, code):
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Given an OAuth Exchange Code, completes the OAuth exchange with the
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linode/linode_api4-python | linode_api4/login_client.py | LinodeLoginClient.expire_token | def expire_token(self, token):
"""
Given a token, makes a request to the authentication server to expire
it immediately. This is considered a responsible way to log out a
user. If you simply remove the session your application has for the
user without expiring their token, the ... | python | def expire_token(self, token):
"""
Given a token, makes a request to the authentication server to expire
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linode/linode_api4-python | linode_api4/objects/profile.py | Profile.grants | def grants(self):
"""
Returns grants for the current user
"""
from linode_api4.objects.account import UserGrants
resp = self._client.get('/profile/grants') # use special endpoint for restricted users
grants = None
if resp is not None:
# if resp is Non... | python | def grants(self):
"""
Returns grants for the current user
"""
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linode/linode_api4-python | linode_api4/objects/profile.py | Profile.add_whitelist_entry | def add_whitelist_entry(self, address, netmask, note=None):
"""
Adds a new entry to this user's IP whitelist, if enabled
"""
result = self._client.post("{}/whitelist".format(Profile.api_endpoint),
data={
"address": address,
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tmm/django-username-email | cuser/forms.py | AuthenticationForm.confirm_login_allowed | def confirm_login_allowed(self, user):
"""
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allow login by active users, and reject login by inactive users.
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dwavesystems/dwave-system | dwave/embedding/chain_breaks.py | broken_chains | def broken_chains(samples, chains):
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Samples as a nS x nV array_like object where nS is the number of samples and nV is the
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... | python | def broken_chains(samples, chains):
"""Find the broken chains.
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samples (array_like):
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dwavesystems/dwave-system | dwave/embedding/chain_breaks.py | discard | def discard(samples, chains):
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dwavesystems/dwave-system | dwave/embedding/chain_breaks.py | majority_vote | def majority_vote(samples, chains):
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samples (array_like):
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dwavesystems/dwave-system | dwave/embedding/chain_breaks.py | weighted_random | def weighted_random(samples, chains):
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samples (array_like):
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dwavesystems/dwave-system | dwave/system/samplers/dwave_sampler.py | DWaveSampler.sample_ising | def sample_ising(self, h, J, **kwargs):
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h (list/dict):
Linear biases of the Ising model. If a list, the list's indices are
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J (dict[(int, int): float]):
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dwavesystems/dwave-system | dwave/system/samplers/dwave_sampler.py | DWaveSampler.sample_qubo | def sample_qubo(self, Q, **kwargs):
"""Sample from the specified QUBO.
Args:
Q (dict):
Coefficients of a quadratic unconstrained binary optimization (QUBO) model.
**kwargs:
Optional keyword arguments for the sampling method, specified per solver ... | python | def sample_qubo(self, Q, **kwargs):
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dwavesystems/dwave-system | dwave/system/samplers/dwave_sampler.py | DWaveSampler.validate_anneal_schedule | def validate_anneal_schedule(self, anneal_schedule):
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dwavesystems/dwave-system | dwave/embedding/utils.py | target_to_source | def target_to_source(target_adjacency, embedding):
"""Derive the source adjacency from an embedding and target adjacency.
Args:
target_adjacency (dict/:class:`networkx.Graph`):
A dict of the form {v: Nv, ...} where v is a node in the target graph and Nv is the
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"""Derive the source adjacency from an embedding and target adjacency.
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dwavesystems/dwave-system | dwave/embedding/utils.py | chain_to_quadratic | def chain_to_quadratic(chain, target_adjacency, chain_strength):
"""Determine the quadratic biases that induce the given chain.
Args:
chain (iterable):
The variables that make up a chain.
target_adjacency (dict/:class:`networkx.Graph`):
Should be a dict of the form {s: ... | python | def chain_to_quadratic(chain, target_adjacency, chain_strength):
"""Determine the quadratic biases that induce the given chain.
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chain (iterable):
The variables that make up a chain.
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dwavesystems/dwave-system | dwave/embedding/utils.py | chain_break_frequency | def chain_break_frequency(samples_like, embedding):
"""Determine the frequency of chain breaks in the given samples.
Args:
samples_like (samples_like/:obj:`dimod.SampleSet`):
A collection of raw samples. 'samples_like' is an extension of NumPy's array_like.
See :func:`dimod.as_s... | python | def chain_break_frequency(samples_like, embedding):
"""Determine the frequency of chain breaks in the given samples.
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dwavesystems/dwave-system | dwave/embedding/utils.py | edgelist_to_adjacency | def edgelist_to_adjacency(edgelist):
"""Converts an iterator of edges to an adjacency dict.
Args:
edgelist (iterable):
An iterator over 2-tuples where each 2-tuple is an edge.
Returns:
dict: The adjacency dict. A dict of the form {v: Nv, ...} where v is a node in a graph and
... | python | def edgelist_to_adjacency(edgelist):
"""Converts an iterator of edges to an adjacency dict.
Args:
edgelist (iterable):
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dwavesystems/dwave-system | dwave/system/composites/tiling.py | TilingComposite.sample | def sample(self, bqm, **kwargs):
"""Sample from the specified binary quadratic model.
Args:
bqm (:obj:`dimod.BinaryQuadraticModel`):
Binary quadratic model to be sampled from.
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Optional keyword arguments for the sampling method, specifie... | python | def sample(self, bqm, **kwargs):
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Binary quadratic model to be sampled from.
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | cache_connect | def cache_connect(database=None):
"""Returns a connection object to a sqlite database.
Args:
database (str, optional): The path to the database the user wishes
to connect to. If not specified, a default is chosen using
:func:`.cache_file`. If the special database name ':memory:'... | python | def cache_connect(database=None):
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | insert_chain | def insert_chain(cur, chain, encoded_data=None):
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Args:
cur (:class:`sqlite3.Cursor`):
An sqlite3 cursor. This function is meant to be run within a :obj:`with` statement.
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | iter_chain | def iter_chain(cur):
"""Iterate over all of the chains in the database.
Args:
cur (:class:`sqlite3.Cursor`):
An sqlite3 cursor. This function is meant to be run within a :obj:`with` statement.
Yields:
list: The chain.
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"""Iterate over all of the chains in the database.
Args:
cur (:class:`sqlite3.Cursor`):
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | insert_system | def insert_system(cur, system_name, encoded_data=None):
"""Insert a system name into the cache.
Args:
cur (:class:`sqlite3.Cursor`):
An sqlite3 cursor. This function is meant to be run within a :obj:`with` statement.
system_name (str):
The unique name of a system
... | python | def insert_system(cur, system_name, encoded_data=None):
"""Insert a system name into the cache.
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | insert_flux_bias | def insert_flux_bias(cur, chain, system, flux_bias, chain_strength, encoded_data=None):
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Args:
cur (:class:`sqlite3.Cursor`):
An sqlite3 cursor. This function is meant to be run within a :obj:`with` statement.
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cur (:class:`sqlite3.Cursor`):
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | iter_flux_bias | def iter_flux_bias(cur):
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | get_flux_biases_from_cache | def get_flux_biases_from_cache(cur, chains, system_name, chain_strength, max_age=3600):
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | insert_graph | def insert_graph(cur, nodelist, edgelist, encoded_data=None):
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | iter_graph | def iter_graph(cur):
"""Iterate over all graphs in the cache.
Args:
cur (:class:`sqlite3.Cursor`): An sqlite3 cursor. This function
is meant to be run within a :obj:`with` statement.
Yields:
tuple: A 2-tuple containing:
list: The nodelist for a graph in the cache.
... | python | def iter_graph(cur):
"""Iterate over all graphs in the cache.
Args:
cur (:class:`sqlite3.Cursor`): An sqlite3 cursor. This function
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | insert_embedding | def insert_embedding(cur, source_nodelist, source_edgelist, target_nodelist, target_edgelist,
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | select_embedding_from_tag | def select_embedding_from_tag(cur, embedding_tag, target_nodelist, target_edgelist):
"""Select an embedding from the given tag and target graph.
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cur (:class:`sqlite3.Cursor`):
An sqlite3 cursor. This function is meant to be run within a :obj:`with` statement.
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dwavesystems/dwave-system | dwave/system/cache/database_manager.py | select_embedding_from_source | def select_embedding_from_source(cur, source_nodelist, source_edgelist,
target_nodelist, target_edgelist):
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dwavesystems/dwave-system | dwave/embedding/pegasus.py | find_clique_embedding | def find_clique_embedding(k, m=None, target_graph=None):
"""Find an embedding of a k-sized clique on a Pegasus graph (target_graph).
This clique is found by transforming the Pegasus graph into a K2,2 Chimera graph and then
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"""Find an embedding of a k-sized clique on a Pegasus graph (target_graph).
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dwavesystems/dwave-system | dwave/embedding/drawing.py | draw_chimera_bqm | def draw_chimera_bqm(bqm, width=None, height=None):
"""Draws a Chimera Graph representation of a Binary Quadratic Model.
If cell width and height not provided assumes square cell dimensions.
Throws an error if drawing onto a Chimera graph of the given dimensions fails.
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bqm (:obj:`dimod.B... | python | def draw_chimera_bqm(bqm, width=None, height=None):
"""Draws a Chimera Graph representation of a Binary Quadratic Model.
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dwavesystems/dwave-system | dwave/embedding/transforms.py | embed_bqm | def embed_bqm(source_bqm, embedding, target_adjacency, chain_strength=1.0,
smear_vartype=None):
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Args:
source_bqm (:obj:`.BinaryQuadraticModel`):
Binary quadratic model to embed.
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dwavesystems/dwave-system | dwave/embedding/transforms.py | embed_ising | def embed_ising(source_h, source_J, embedding, target_adjacency, chain_strength=1.0):
"""Embed an Ising problem onto a target graph.
Args:
source_h (dict[variable, bias]/list[bias]):
Linear biases of the Ising problem. If a list, the list's indices are used as
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"""Embed an Ising problem onto a target graph.
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source_h (dict[variable, bias]/list[bias]):
Linear biases of the Ising problem. If a list, the list's indices are used as
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dwavesystems/dwave-system | dwave/embedding/transforms.py | embed_qubo | def embed_qubo(source_Q, embedding, target_adjacency, chain_strength=1.0):
"""Embed a QUBO onto a target graph.
Args:
source_Q (dict[(variable, variable), bias]):
Coefficients of a quadratic unconstrained binary optimization (QUBO) model.
embedding (dict):
Mapping from ... | python | def embed_qubo(source_Q, embedding, target_adjacency, chain_strength=1.0):
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source_Q (dict[(variable, variable), bias]):
Coefficients of a quadratic unconstrained binary optimization (QUBO) model.
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dwavesystems/dwave-system | dwave/embedding/transforms.py | unembed_sampleset | def unembed_sampleset(target_sampleset, embedding, source_bqm,
chain_break_method=None, chain_break_fraction=False):
"""Unembed the samples set.
Construct a sample set for the source binary quadratic model (BQM) by
unembedding the given samples from the target BQM.
Args:
... | python | def unembed_sampleset(target_sampleset, embedding, source_bqm,
chain_break_method=None, chain_break_fraction=False):
"""Unembed the samples set.
Construct a sample set for the source binary quadratic model (BQM) by
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dwavesystems/dwave-system | dwave/system/composites/embedding.py | _adjacency_to_edges | def _adjacency_to_edges(adjacency):
"""determine from an adjacency the list of edges
if (u, v) in edges, then (v, u) should not be"""
edges = set()
for u in adjacency:
for v in adjacency[u]:
try:
edge = (u, v) if u <= v else (v, u)
except TypeError:
... | python | def _adjacency_to_edges(adjacency):
"""determine from an adjacency the list of edges
if (u, v) in edges, then (v, u) should not be"""
edges = set()
for u in adjacency:
for v in adjacency[u]:
try:
edge = (u, v) if u <= v else (v, u)
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dwavesystems/dwave-system | dwave/system/composites/embedding.py | _embed_state | def _embed_state(embedding, state):
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return {u: state[v] for v, chain in embedding.items() for u in chain} | python | def _embed_state(embedding, state):
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dwavesystems/dwave-system | dwave/system/composites/embedding.py | EmbeddingComposite.parameters | def parameters(self):
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dwavesystems/dwave-system | dwave/system/composites/embedding.py | EmbeddingComposite.sample | def sample(self, bqm, chain_strength=1.0, chain_break_fraction=True, **parameters):
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Also set parameters for handling a chain, the set of vertices in a target graph that
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dwavesystems/dwave-system | dwave/system/composites/embedding.py | FixedEmbeddingComposite.sample | def sample(self, bqm, chain_strength=1.0, chain_break_fraction=True, **parameters):
"""Sample from the provided binary quadratic model.
Also set parameters for handling a chain, the set of vertices in a target graph that
represents a source-graph vertex; when a D-Wave system is the sampler, it ... | python | def sample(self, bqm, chain_strength=1.0, chain_break_fraction=True, **parameters):
"""Sample from the provided binary quadratic model.
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dwavesystems/dwave-system | dwave/system/composites/embedding.py | LazyFixedEmbeddingComposite.sample | def sample(self, bqm, chain_strength=1.0, chain_break_fraction=True, **parameters):
"""Sample the binary quadratic model.
Note: At the initial sample(..) call, it will find a suitable embedding and initialize the remaining attributes
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | _accumulate_random | def _accumulate_random(count, found, oldthing, newthing):
"""This performs on-line random selection.
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o_1,c_1; o_2,c_2; ...
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o_1,c_1; o_2,c_2; ...
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | _bulk_to_linear | def _bulk_to_linear(M, N, L, qubits):
"Converts a list of chimera coordinates to linear indices."
return [2 * L * N * x + 2 * L * y + L * u + k for x, y, u, k in qubits] | python | def _bulk_to_linear(M, N, L, qubits):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | _to_linear | def _to_linear(M, N, L, q):
"Converts a qubit in chimera coordinates to its linear index."
(x, y, u, k) = q
return 2 * L * N * x + 2 * L * y + L * u + k | python | def _to_linear(M, N, L, q):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | _bulk_to_chimera | def _bulk_to_chimera(M, N, L, qubits):
"Converts a list of linear indices to chimera coordinates."
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | _to_chimera | def _to_chimera(M, N, L, q):
"Converts a qubit's linear index to chimera coordinates."
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | _chimera_neighbors | def _chimera_neighbors(M, N, L, q):
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n = [(x, y, 1 - u, l) for l in range(L)]
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if x:
n.append((x - 1, y, u, k))
if x < M - 1:
n.append((x + 1, y, u, k))
else:
... | python | def _chimera_neighbors(M, N, L, q):
"Returns a list of neighbors of (x,y,u,k) in a perfect :math:`C_{M,N,L}`"
(x, y, u, k) = q
n = [(x, y, 1 - u, l) for l in range(L)]
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | random_processor | def random_processor(M, N, L, qubit_yield, num_evil=0):
"""A utility function that generates a random :math:`C_{M,N,L}` missing some
percentage of its qubits.
INPUTS:
M,N,L: the chimera parameters
qubit_yield: ratio (0 <= qubit_yield <= 1) of #{qubits}/(2*M*N*L)
num_evil: number of ... | python | def random_processor(M, N, L, qubit_yield, num_evil=0):
"""A utility function that generates a random :math:`C_{M,N,L}` missing some
percentage of its qubits.
INPUTS:
M,N,L: the chimera parameters
qubit_yield: ratio (0 <= qubit_yield <= 1) of #{qubits}/(2*M*N*L)
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.vline_score | def vline_score(self, x, ymin, ymax):
"""Returns the number of unbroken paths of qubits
>>> [(x,y,1,k) for y in range(ymin,ymax+1)]
for :math:`k = 0,1,\cdots,L-1`. This is precomputed for speed.
"""
return self._vline_score[x, ymin, ymax] | python | def vline_score(self, x, ymin, ymax):
"""Returns the number of unbroken paths of qubits
>>> [(x,y,1,k) for y in range(ymin,ymax+1)]
for :math:`k = 0,1,\cdots,L-1`. This is precomputed for speed.
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.hline_score | def hline_score(self, y, xmin, xmax):
"""Returns the number of unbroken paths of qubits
>>> [(x,y,0,k) for x in range(xmin,xmax+1)]
for :math:`k = 0,1,\cdots,L-1`. This is precomputed for speed.
"""
return self._hline_score[y, xmin, xmax] | python | def hline_score(self, y, xmin, xmax):
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>>> [(x,y,0,k) for x in range(xmin,xmax+1)]
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor._compute_vline_scores | def _compute_vline_scores(self):
"""Does the hard work to prepare ``vline_score``.
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vline_score = {}
for x in range(M):
laststart = [0 if (x, 0, 1, k) in self else None for k in range(L)]
for y in range(N):
... | python | def _compute_vline_scores(self):
"""Does the hard work to prepare ``vline_score``.
"""
M, N, L = self.M, self.N, self.L
vline_score = {}
for x in range(M):
laststart = [0 if (x, 0, 1, k) in self else None for k in range(L)]
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor._compute_hline_scores | def _compute_hline_scores(self):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor._compute_biclique_sizes | def _compute_biclique_sizes(self, recompute=False):
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recompute: if ``True``, then we dump the existing cache and compute
all biclique sizes f... | python | def _compute_biclique_sizes(self, recompute=False):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.biclique_size | def biclique_size(self, xmin, xmax, ymin, ymax):
"""Returns the size parameters ``(m,n)`` of the complete bipartite graph
:math:`K_{m,n}` comprised of ``m`` unbroken chains of horizontally-aligned qubits
and ``n`` unbroken chains of vertically-aligned qubits (known as line
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... | python | def biclique_size(self, xmin, xmax, ymin, ymax):
"""Returns the size parameters ``(m,n)`` of the complete bipartite graph
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.biclique | def biclique(self, xmin, xmax, ymin, ymax):
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xmin,xmax,ymin,ymax: integers d... | python | def biclique(self, xmin, xmax, ymin, ymax):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor._contains_line | def _contains_line(self, line):
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NOTE: this function assumes that ``line`` is a list or tuple of
qubits wh... | python | def _contains_line(self, line):
"""Test if a chain of qubits is completely contained in ``self``. In
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.maximum_vline_bundle | def maximum_vline_bundle(self, x0, y0, y1):
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INPUTS:
y0,x0,x1: int
OUTPUT:
list of lists of qubits
"""
y_range = range(y1, y0 - 1, -1) if y0 < ... | python | def maximum_vline_bundle(self, x0, y0, y1):
"""Compute a maximum set of vertical lines in the unit cells ``(x0,y)``
for :math:`y0 \leq y \leq y1`.
INPUTS:
y0,x0,x1: int
OUTPUT:
list of lists of qubits
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.maximum_hline_bundle | def maximum_hline_bundle(self, y0, x0, x1):
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INPUTS:
y0,x0,x1: int
OUTPUT:
list of lists of qubits
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x_range = range(x0, x1 + 1) if x0 < x1 ... | python | def maximum_hline_bundle(self, y0, x0, x1):
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y0,x0,x1: int
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list of lists of qubits
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.maximum_ell_bundle | def maximum_ell_bundle(self, ell):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor._combine_clique_scores | def _combine_clique_scores(self, rscore, hbar, vbar):
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attained by the already-placed ells, together with the ell block
defined by ``hbar = (y0,xmin,xmax)``, and ``vbar = (x0,ymin,ymax)``.
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.maxCliqueWithRectangle | def maxCliqueWithRectangle(self, R, maxCWR):
"""This does the dirty work for :func:`nativeCliqueEmbed`. Not meant to be
understood or called on its own. Guaranteed to maintain the inductive
hypothesis that ``maxCWR`` is optimal. We put in the tiniest amount of
effort to return a unifo... | python | def maxCliqueWithRectangle(self, R, maxCWR):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.nativeCliqueEmbed | def nativeCliqueEmbed(self, width):
"""Compute a maximum-sized native clique embedding in an induced
subgraph of chimera with all chainlengths ``width+1``.
INPUTS:
width: width of the squares to search, also `chainlength`-1
OUTPUT:
score: the score for the retur... | python | def nativeCliqueEmbed(self, width):
"""Compute a maximum-sized native clique embedding in an induced
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width: width of the squares to search, also `chainlength`-1
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.largestNativeClique | def largestNativeClique(self, max_chain_length=None):
"""Returns the largest native clique embedding we can find on the
processor, with the shortest chainlength possible (for that
clique size).
OUTPUT:
score: the score for the returned clique (just ``len(clique)``
... | python | def largestNativeClique(self, max_chain_length=None):
"""Returns the largest native clique embedding we can find on the
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score: the score for the returned clique (just ``len(clique)``
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | eden_processor.largestNativeBiClique | def largestNativeBiClique(self, chain_imbalance=0, max_chain_length=None):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor._compute_all_deletions | def _compute_all_deletions(self):
"""Returns all minimal edge covers of the set of evil edges.
"""
minimum_evil = []
for disabled_qubits in map(set, product(*self._evil)):
newmin = []
for s in minimum_evil:
if s < disabled_qubits:
... | python | def _compute_all_deletions(self):
"""Returns all minimal edge covers of the set of evil edges.
"""
minimum_evil = []
for disabled_qubits in map(set, product(*self._evil)):
newmin = []
for s in minimum_evil:
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor._subprocessor | def _subprocessor(self, disabled_qubits):
"""Create a subprocessor by deleting a set of qubits. We assume
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor._map_to_processors | def _map_to_processors(self, f, objective):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor._objective_bestscore | def _objective_bestscore(self, old, new):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor._find_evil | def _find_evil(self):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor.largestNativeClique | def largestNativeClique(self, max_chain_length=None):
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... | python | def largestNativeClique(self, max_chain_length=None):
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... | [
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor.nativeCliqueEmbed | def nativeCliqueEmbed(self, width):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor.largestNativeBiClique | def largestNativeBiClique(self, chain_imbalance=0, max_chain_length=None):
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dwavesystems/dwave-system | dwave/embedding/polynomialembedder.py | processor._translate | def _translate(self, embedding):
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dwavesystems/dwave-system | dwave/system/composites/virtual_graph.py | _validate_chain_strength | def _validate_chain_strength(sampler, chain_strength):
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dwavesystems/dwave-system | dwave/system/composites/virtual_graph.py | VirtualGraphComposite.sample | def sample(self, bqm, apply_flux_bias_offsets=True, **kwargs):
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Args:
h (list/dict):
Linear biases of the Ising model. If a list, the list's indices
are used as variable labels.
J (dict of (int, int):float):
... | python | def sample(self, bqm, apply_flux_bias_offsets=True, **kwargs):
"""Sample from the given Ising model.
Args:
h (list/dict):
Linear biases of the Ising model. If a list, the list's indices
are used as variable labels.
J (dict of (int, int):float):
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Linear biases of the Ising model. If a list, the list's indices
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dwavesystems/dwave-system | dwave/system/flux_bias_offsets.py | get_flux_biases | def get_flux_biases(sampler, embedding, chain_strength, num_reads=1000, max_age=3600):
"""Get the flux bias offsets for sampler and embedding.
Args:
sampler (:obj:`.DWaveSampler`):
A D-Wave sampler.
embedding (dict[hashable, iterable]):
Mapping from a source graph to th... | python | def get_flux_biases(sampler, embedding, chain_strength, num_reads=1000, max_age=3600):
"""Get the flux bias offsets for sampler and embedding.
Args:
sampler (:obj:`.DWaveSampler`):
A D-Wave sampler.
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dwavesystems/dwave-system | dwave/embedding/chimera.py | find_clique_embedding | def find_clique_embedding(k, m, n=None, t=None, target_edges=None):
"""Find an embedding for a clique in a Chimera graph.
Given a target :term:`Chimera` graph size, and a clique (fully connect graph),
attempts to find an embedding.
Args:
k (int/iterable):
Clique to embed. If k is a... | python | def find_clique_embedding(k, m, n=None, t=None, target_edges=None):
"""Find an embedding for a clique in a Chimera graph.
Given a target :term:`Chimera` graph size, and a clique (fully connect graph),
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Clique to embed. If k is a... | [
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dwavesystems/dwave-system | dwave/embedding/chimera.py | find_biclique_embedding | def find_biclique_embedding(a, b, m, n=None, t=None, target_edges=None):
"""Find an embedding for a biclique in a Chimera graph.
Given a target :term:`Chimera` graph size, and a biclique (a bipartite graph where every
vertex in a set in connected to all vertices in the other set), attempts to find an embed... | python | def find_biclique_embedding(a, b, m, n=None, t=None, target_edges=None):
"""Find an embedding for a biclique in a Chimera graph.
Given a target :term:`Chimera` graph size, and a biclique (a bipartite graph where every
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